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A targeted proteomics-based pipeline for verification of biomarkers in plasma

High-throughput technologies can now identify hundreds of candidate protein biomarkers for any disease with relative ease. However, because there are no assays for the majority of proteins and de novo immunoassay development is prohibitively expensive, few candidate biomarkers are tested in clinical... Full description

Journal Title: Nature biotechnology 2011-07, Vol.29 (7), p.625-634
Main Author: Paulovich, Amanda G
Other Authors: Whiteaker, Jeffrey R , Lin, Chenwei , Kennedy, Jacob , Hou, Liming , Trute, Mary , Sokal, Izabela , Yan, Ping , Schoenherr, Regine M , Zhao, Lei , Voytovich, Uliana J , Kelly-Spratt, Karen S , Krasnoselsky, Alexei , Gafken, Philip R , Hogan, Jason M , Jones, Lisa A , Wang, Pei , Amon, Lynn , Chodosh, Lewis A , Nelson, Peter S , McIntosh, Martin W , Kemp, Christopher J
Format: Electronic Article Electronic Article
Language: English
Subjects:
Publisher: New York, NY: Nature Publishing Group
ID: ISSN: 1087-0156
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recordid: cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_3232032
title: A targeted proteomics-based pipeline for verification of biomarkers in plasma
format: Article
creator:
  • Paulovich, Amanda G
  • Whiteaker, Jeffrey R
  • Lin, Chenwei
  • Kennedy, Jacob
  • Hou, Liming
  • Trute, Mary
  • Sokal, Izabela
  • Yan, Ping
  • Schoenherr, Regine M
  • Zhao, Lei
  • Voytovich, Uliana J
  • Kelly-Spratt, Karen S
  • Krasnoselsky, Alexei
  • Gafken, Philip R
  • Hogan, Jason M
  • Jones, Lisa A
  • Wang, Pei
  • Amon, Lynn
  • Chodosh, Lewis A
  • Nelson, Peter S
  • McIntosh, Martin W
  • Kemp, Christopher J
subjects:
  • Animals
  • Article
  • Biological and medical sciences
  • Biological assays
  • Biological markers
  • Biomarkers
  • Biomarkers, Tumor - blood
  • Biotechnology
  • Blood Chemical Analysis - methods
  • Breast cancer
  • Fundamental and applied biological sciences. Psychology
  • Health. Pharmaceutical industry
  • Industrial applications and implications. Economical aspects
  • Mass spectrometry
  • Mass Spectrometry - methods
  • Mice
  • Miscellaneous
  • Neoplasm Proteins - blood
  • Neoplasms, Experimental - blood
  • Peptide Mapping - methods
  • Physiological aspects
  • Plasma
  • Proteins
  • Proteome - analysis
  • Proteomics
  • Proteomics - methods
  • Usage
ispartof: Nature biotechnology, 2011-07, Vol.29 (7), p.625-634
description: High-throughput technologies can now identify hundreds of candidate protein biomarkers for any disease with relative ease. However, because there are no assays for the majority of proteins and de novo immunoassay development is prohibitively expensive, few candidate biomarkers are tested in clinical studies. We tested whether the analytical performance of a biomarker identification pipeline based on targeted mass spectrometry would be sufficient for data-dependent prioritization of candidate biomarkers, de novo development of assays and multiplexed biomarker verification. We used a data-dependent triage process to prioritize a subset of putative plasma biomarkers from >1,000 candidates previously identified using a mouse model of breast cancer. Eighty-eight novel quantitative assays based on selected reaction monitoring mass spectrometry were developed, multiplexed and evaluated in 80 plasma samples. Thirty-six proteins were verified as being elevated in the plasma of tumor-bearing animals. The analytical performance of this pipeline suggests that it should support the use of an analogous approach with human samples.
language: eng
source:
identifier: ISSN: 1087-0156
fulltext: no_fulltext
issn:
  • 1087-0156
  • 1546-1696
url: Link


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creatorcontribPaulovich, Amanda G ; Whiteaker, Jeffrey R ; Lin, Chenwei ; Kennedy, Jacob ; Hou, Liming ; Trute, Mary ; Sokal, Izabela ; Yan, Ping ; Schoenherr, Regine M ; Zhao, Lei ; Voytovich, Uliana J ; Kelly-Spratt, Karen S ; Krasnoselsky, Alexei ; Gafken, Philip R ; Hogan, Jason M ; Jones, Lisa A ; Wang, Pei ; Amon, Lynn ; Chodosh, Lewis A ; Nelson, Peter S ; McIntosh, Martin W ; Kemp, Christopher J
descriptionHigh-throughput technologies can now identify hundreds of candidate protein biomarkers for any disease with relative ease. However, because there are no assays for the majority of proteins and de novo immunoassay development is prohibitively expensive, few candidate biomarkers are tested in clinical studies. We tested whether the analytical performance of a biomarker identification pipeline based on targeted mass spectrometry would be sufficient for data-dependent prioritization of candidate biomarkers, de novo development of assays and multiplexed biomarker verification. We used a data-dependent triage process to prioritize a subset of putative plasma biomarkers from >1,000 candidates previously identified using a mouse model of breast cancer. Eighty-eight novel quantitative assays based on selected reaction monitoring mass spectrometry were developed, multiplexed and evaluated in 80 plasma samples. Thirty-six proteins were verified as being elevated in the plasma of tumor-bearing animals. The analytical performance of this pipeline suggests that it should support the use of an analogous approach with human samples.
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subjectAnimals ; Article ; Biological and medical sciences ; Biological assays ; Biological markers ; Biomarkers ; Biomarkers, Tumor - blood ; Biotechnology ; Blood Chemical Analysis - methods ; Breast cancer ; Fundamental and applied biological sciences. Psychology ; Health. Pharmaceutical industry ; Industrial applications and implications. Economical aspects ; Mass spectrometry ; Mass Spectrometry - methods ; Mice ; Miscellaneous ; Neoplasm Proteins - blood ; Neoplasms, Experimental - blood ; Peptide Mapping - methods ; Physiological aspects ; Plasma ; Proteins ; Proteome - analysis ; Proteomics ; Proteomics - methods ; Usage
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descriptionHigh-throughput technologies can now identify hundreds of candidate protein biomarkers for any disease with relative ease. However, because there are no assays for the majority of proteins and de novo immunoassay development is prohibitively expensive, few candidate biomarkers are tested in clinical studies. We tested whether the analytical performance of a biomarker identification pipeline based on targeted mass spectrometry would be sufficient for data-dependent prioritization of candidate biomarkers, de novo development of assays and multiplexed biomarker verification. We used a data-dependent triage process to prioritize a subset of putative plasma biomarkers from >1,000 candidates previously identified using a mouse model of breast cancer. Eighty-eight novel quantitative assays based on selected reaction monitoring mass spectrometry were developed, multiplexed and evaluated in 80 plasma samples. Thirty-six proteins were verified as being elevated in the plasma of tumor-bearing animals. The analytical performance of this pipeline suggests that it should support the use of an analogous approach with human samples.
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titleA targeted proteomics-based pipeline for verification of biomarkers in plasma
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abstractHigh-throughput technologies can now identify hundreds of candidate protein biomarkers for any disease with relative ease. However, because there are no assays for the majority of proteins and de novo immunoassay development is prohibitively expensive, few candidate biomarkers are tested in clinical studies. We tested whether the analytical performance of a biomarker identification pipeline based on targeted mass spectrometry would be sufficient for data-dependent prioritization of candidate biomarkers, de novo development of assays and multiplexed biomarker verification. We used a data-dependent triage process to prioritize a subset of putative plasma biomarkers from >1,000 candidates previously identified using a mouse model of breast cancer. Eighty-eight novel quantitative assays based on selected reaction monitoring mass spectrometry were developed, multiplexed and evaluated in 80 plasma samples. Thirty-six proteins were verified as being elevated in the plasma of tumor-bearing animals. The analytical performance of this pipeline suggests that it should support the use of an analogous approach with human samples.
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